I am currently a PhD student in the Machine Learning Group at The University of Manchester, working on physics-informed probabilistic deep learning under the supervision of Dr Mauricio Álvarez. Previously, I obtained my masters and undergraduate degrees in the Computer Science and Physics departments respectively at The University of Sheffield, and I have also worked as an analyst in the energy sector and as a summer research intern at Spotify.
Previously known as Thomas M. McDonald.
Download my CV.
- Gaussian processes
- Bayesian deep learning
- Physics-informed ML
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PhD in Computer Science, 2024
The University of Manchester
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MSc in Data Analytics, 2020
The University of Sheffield
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BSc (Hons) in Physics, 2018
The University of Sheffield
Publications
Experience
- I spent the summer working within Tech Research at Spotify on a project which leveraged Bayesian filtering and Thompson sampling to provide podcast recommendations which drive long-term user engagement. This work was presented at KDD 2023.
- I have worked as a GTA on a number of different courses within the Faculty of Engineering, and currently assist with postgraduate-level courses focused on machine learning, handling data at scale using Spark and High Performance Computing infrastructure.
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My role involved employing statistical modelling to forecast national non-commodity cost components and mitigate the level of risk involved in signing energy supply contracts.
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Implemented seasonal ARIMA forecasting models in Python, with the models routinely returning <1% error on predictions made three months ahead of time.
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Improved functionality of the VBA gas and electricity price matrices.